scholarly journals Geospatial assessment of land use and land cover dynamics in the mid-zone of Ghana

2020 ◽  
Vol 62 (4) ◽  
pp. 288-305
Author(s):  
Addo Koranteng ◽  
Isaac Adu-Poku ◽  
Emmanuel Donkor ◽  
Tomasz Zawiła-Niedźwiecki
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Forest Cover ◽  
Anthropogenic Activities ◽  
Arable Land ◽  
Rapid Urbanization ◽  
The Past ◽  
Open Forest

AbstractLand use and land cover (LULC) terrain in Ghana has undergone profound changes over the past years emanating mainly from anthropogenic activities, which have impacted countrywide and sub-regional environment. This study is a comprehensive analysis via integrated approach of geospatial procedures such as Remote Sensing (RS) and Geographic Information System (GIS) of past, present and future LULC from satellite imagery covering Ghana’s Ashanti regional capital (Kumasi) and surrounding districts. Multi-temporal satellite imagery data sets of four different years, 1990 (Landsat TM), 2000 (Landsat ETM+), 2010 (Alos and Disaster Monitoring Constellation-DMC) and 2020 (SENTINEL), spanning over a 30-year period were mapped. Five major LULC categories – Closed Forest, Open Forest, Agriculture, Built-up and Water – were delineated premised on the prevailing geographical settings, field study and remote sensing data. Markov Cellular Automata modelling was applied to predict the probable LULC change consequence for the next 20 years (2040). The study revealed that both Open Forest and Agriculture class categories decreased 51.98 to 38.82 and 27.48 to 20.11, respectively. Meanwhile, Built-up class increased from 4.8% to 24.8% (over 500% increment from 1990 to 2020). Rapid urbanization caused the depletion of forest cover and conversion of farmlands into human settlements. The 2040 forecast map showed an upward increment in the Built-up area up to 35.2% at the expense of other LULC class categories. This trend from the past to the forecasted future would demand that judicious LULC resolutions have to be made to keep Ghana’s forest cover, provide arable land for farming activities and alleviate the effects of climate change.

scholarly journals Land Use Land Cover Analysis using Geospatial Techniques

2021 ◽  
Vol 9 (8) ◽  
pp. 2561-2566
Author(s):  
Babita Singh
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Images ◽  
Anthropogenic Activities ◽  
Google Earth ◽  
Landscape Configuration ◽  
Landsat 8 ◽  
Visual Interpretation ◽  
Open Forest

Abstract: Remote sensing and Geographic information system (GIS) techniques can be used for the changing pattern of landscape. The study was conducted in Dehradun, Haridwar and Pauri Garhwal Districts of Uttarakhand State, India. In order to understand dynamics of landscape and to examine changes in the land use/cover due to anthropogenic activities, two satellite images (Landsat 5 and Landsat 8) for 1998 and 2020 were used. Google Earth Engine was used to perform supervised classification. Spectral indices (NDVI, MNDWI, SAVI, NDBI) were calculated in order to identify land cover classes. Both 1998 and 2020 satellite images were classified broadly into six classes namely agriculture, built-up, dense forest, open forest, scrub and waterbody. Using high resolution google earth satellite images and visual interpretation, overall accuracy assessment was performed. For land cover/use change analysis, these images were imported to GIS platform. Landscape configuration was observed by calculating various landscape metrices Images. It was observed that scrub land area had increased from 11 % to 14 % but a decrease in agriculture by 4.65 %. The increased value of NP, PD, PLAND, LPI and decrease in AI landscape indices shows that land fragmentation had increased since 1998. The most fragmented classes were scrub (PD - 3.32 to 5.18) and open forest (PD - 3.57 to 5.07). Decrease in AI for open forest, agriculture, built-up indicated that more fragmented patches of these classes were present. The result confirmed increase in the fragmentation of landscape from 1998 onwards. Keywords: GIS, LULC, landscape metrics, Remote Sensing

scholarly journals Geo-spatial Analysis of Land Use Land Cover (LULC) Changes in Oluwa Forest Reserve and its Environs

2021 ◽  
Vol 25 (7) ◽  
pp. 1257-1262
Author(s):  
E.O. Toyinbo ◽  
R.A. Fasasi ◽  
C.F. Agbor ◽  
C.O. Fakorede
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Forest Cover ◽  
Anthropogenic Activities ◽  
Management Tool ◽  
Primary Forest ◽  
Land Use Land Cover ◽  
Forest Reserve ◽  
Lulc Changes

Mankind’s existence and modification of the landscape have had a profound effect on the natural environment. Anthropogenic activities such as agriculture, mining, deforestation and construction have influenced the shifting patterns of land use. This has resulted in a significant effect on local weather and climate. The use of remote sensing data in recent times has been of immense help in monitoring the changing pattern of vegetation. Therefore this study utilized remote sensing and geographic information system (GIS) methods to identify factors responsible for land use land cover (LULC) changes in Oluwa Forest Reserve between 1984 and 2017. The result showed that Primary forest was reduced by about 5% between 1984 and 2000 and by about 12% between 2000 and 2017 and the non-forest got increased by about 4% and 2% from 1984 to 2000 and from 2000 to 2017 respectively. Future forecast shows that primary forest will decrease by about 3% while the non-forest will increase by 5% by 2034. The results also revealed that the changes in forest cover between 2000 and 2017 were actively influenced by the closeness of settlements to the forest. It is therefore recommended that the findings of this study should be adopted by relevant authorities as a useful forest management tool.

scholarly journals Land Use and Land Cover Changes, and Environment and Risk Evaluation of Dujiangyan City (SW China) Using Remote Sensing and GIS Techniques

2018 ◽  
Vol 10 (12) ◽  
pp. 4631 ◽  
Author(s):  
Biswajit Nath ◽  
Zheng Niu ◽  
Ramesh Singh
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Forest Cover ◽  
Landscape Planning ◽  
Anthropogenic Activities ◽  
Remote Sensing And Gis ◽  
Geographical Information ◽  
Lulc Change ◽  
2008 Wenchuan Earthquake

Understanding of the Land Use and Land Cover (LULC) change, its transitions and Landscape risk (LR) evaluation in earthquake-affected areas is important for planning and urban sustainability. In the present study, we have considered Dujiangyan City and its Environs (DCEN), a seismic-prone area close to the 2008 Wenchuan earthquake (8.0 Mw) during 2007–2018. Five different multi-temporal data sets for the years 2007, 2008, 2010, 2015, and 2018 were considered for LULC mapping, followed by the maximum likelihood supervised classification technique. The individual LULC maps were further used in four time periods, i.e., 2007–2018, 2008–2018, 2010–2018, and 2015–2018, to evaluate the Land Use and Land Cover Transitions (LULCT) using combined remote sensing and GIS (Geographical Information System). Furthermore, multi-criteria evaluation (MCE) techniques were applied for LR mapping. The results of the LULC change data indicate that built-up, agricultural area, and forest cover are the prime categories that had been changed by the natural and anthropogenic activities. LULCT, along with multi-parameters, are suggested to avoid development in fault-existing areas that are seismically vulnerable for future landscape planning in a sustainable manner.

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

scholarly journals ALTERAÇÃO NA COBERTURA FLORESTAL DA REGIÃO NOROESTE DA AMAZÔNIA MATOGROSSENSE

Nativa ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 520
Author(s):  
Luani Rosa de Oliveira Piva ◽  
Rorai Pereira Martins Neto
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Forest Cover ◽  
Forest Conversion ◽  
Landsat 8 ◽  
Amazon Forest ◽  
Landsat 8 Oli ◽  
Mato Grosso ◽  
The Past ◽  
Landsat 5 Tm

Nos últimos anos, a intensificação das atividades antrópicas modificadoras da cobertura vegetal do solo em território brasileiro vem ocorrendo em larga escala. Para fins de monitoramento das alterações da cobertura florestal, as técnicas de Sensoriamento Remoto da vegetação são ferramentas imprescindíveis, principalmente em áreas extensas e de difícil acesso, como é o caso da Amazônia brasileira. Neste sentido, objetivou-se com este trabalho identificar as mudanças no uso e cobertura do solo no período de 20 anos nos municípios de Aripuanã e Rondolândia, Noroeste do Mato Grosso, visando quantificar as áreas efetivas que sofreram alterações. Para tal, foram utilizadas técnicas de classificação digital de imagens Landsat 5 TM e Landsat 8 OLI em três diferentes datas (1995, 2005 e 2015) e, posteriormente, realizada a detecção de mudanças para o uso e cobertura do solo. A classificação digital apresentou resultados excelentes, com índice Kappa acima de 0,80 para os mapas gerados, indicando ser uma ferramenta potencial para o uso e cobertura do solo. Os resultados denotaram uma conversão de áreas florestais principalmente para atividades antrópicas agrícolas, na ordem de 472 km², o que representa uma perda de 1,3% de superfície de floresta amazônica na região de estudo.Palavras-chave: conversão de áreas florestais; uso e cobertura do solo; classificação digital; análise multitemporal. CHANGE IN FOREST COVER OF THE NORTHWEST REGION OF AMAZON IN MATO GROSSO STATE ABSTRACT: In the past few years, the intensification of anthropic activities that modify the soil-vegetation cover in Brazil’s land has been occurring on a large scale. To monitor the forest cover changes, the techniques of Remote Sensing of vegetation are essential tools, especially in large areas and with difficult access, as is the case of the Brazilian Amazon. The aim of this work was to identify the changes in land use and land cover, over the past 20 years, in the municipalities of Aripuanã and Rondolândia, Northwest of Mato Grosso State, in order to quantify the effective altered areas. Landsat 5 TM and Landsat 8 OLI digital classification images techniques were used in three different dates (1995, 2005 and 2015) and, later, the detection to the land use and land cover changes. The digital classification showed excellent results, with kappa index above 0.80 for the generated maps, indicating the digital classification as a potential tool for land use and land cover. Results reflect the conversion of forest areas mainly for agricultural activities, in the order of 472 km², representing a loss of 1.3% of Amazon forest surface in the study region.Keywords: forest conversion; land use and land cover; digital classification; multitemporal analysis.

scholarly journals Understanding of Forest Cover Dynamics in Traditional Landscapes: Mapping Trajectories of Changes in Mountain Territories (1824–2016), on the Example of Jeleniogórska Basin, Poland

Forests ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 867 ◽  
Author(s):  
Justyna Jaworek-Jakubska ◽  
Maciej Filipiak ◽  
Anna Napierała-Filipiak
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Forest Cover ◽  
Cultural Landscapes ◽  
Local Development ◽  
Arable Land ◽  
Rate Of Change ◽  
Aerial Photographs ◽  
Depth Analysis

Though on a global scale, for ecological reasons, increased forest cover is universally regarded as positive, on a local scale, the reforestation of arable land may pose threats to cultural landscapes by removing characteristic landscape features. Particularly vulnerable are marginal rural areas, e.g., mountain regions, where most traditional land use systems have survived and which are subject to the most spectacular land use change. The purpose of this article is to draw attention to the issue of the management of forest cover in historical cultural landscapes in mountain territories in Poland within the context of widespread land use change in Eastern Europe. Land cover data were obtained from historical and contemporary aerial photographs, as well as topographic maps from five time points between 1824 and 2016. The study was conducted by means of spatio-temporal forest cover trajectory analysis (LCTA), transition and time–depth analysis, and land cover change calculations that were made by means of ArcGIS. Our research indicates that the rate of change has risen considerably in the last two decades, and the current share of forest cover is much bigger than that reflected in the official data. Eight principal forest cover trajectory types were identified. The biggest area is occupied by woodland of long-term stability. Another large group is constituted by forests created on the basis of arable land and grassland as a result of simple conversion at one point in time, mainly in the years 1824–1886 and 1939–1994. At the same time, a sizeable group is made up by areas that have been subject to unplanned cyclical or dynamic changes during various periods. A very important group is comprised new forests that were created in 1994–2016, predominantly as a result of natural succession, that are often not included in official land classifications. The constant expansion of woodlands has led to a shrinking of historical former coppice woodlands. This indicates that the current landscape management mechanisms in Poland are inadequate for protecting the cultural landscape. The barriers include the lack of intersectoral cooperation and the overlooking of the historical context of landscapes. The present situation calls not only for verification of the existing forest policy but also for increasing the role and engagement of local communities, as well as making comprehensive local development plans, all of which may be helped by the findings of our study and of similar research.

scholarly journals MULTITEMPORAL ANALYSIS OF FOREST COVER CHANGE USING REMOTE SENSING AND GIS OF KANHA TIGER RESERVE, CENTRAL INDIA

2018 ◽  
Vol XLII-5 ◽  
pp. 211-219 ◽  
Author(s):  
R. M. Devi ◽  
B. Sinha ◽  
J. Bisaria ◽  
S. Saran
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Forest Cover ◽  
Central India ◽  
Adaptation Strategies ◽  
Land Use Land Cover ◽  
Tiger Reserve ◽  
The Impact

<p><strong>Abstract.</strong> Forest ecosystems play a key role in global ecological balance and provide a variety of tangible and intangible ecosystem services that support the livelihoods of rural poor. In addition to the anthropogenic pressure on the forest resources, climate change is also impacting vegetation productivity, biomass and phenological patterns of the forest. There are many studies reported all over the world which use change in Land Use Land Cover (LULC) to assess the impact of climate change on the forest. Land use change (LC) refers to any anthropogenic or natural changes in the terrestrial ecosystem at a variety of spatial or temporal scale. Changes in LULC induced by any causes (natural/anthropogenic) play a major role in global as well as regional scale pattern which in turn affects weather and climate. Remote sensing (RS) data along with Geographic Information System (GIS) help in inventorying, mapping and monitoring of earth resources for effective and sustainable landscape management of forest areas. Accurate information about the current and past LULC including natural forest cover along with accurate means of monitoring the changes are very necessary to design future adaptation strategies and formulation of policies in tune of climate change. Therefore, this study attempts to analyze the changes of LULC of Kanha Tiger Reserve (KTR) due to climate change. The rationale for selecting KTR is to have a largely intact forest area without any interference so that any change in LULC could be attributed to the impact of climate change. The change analysis depicted changes in land use land cover (LULC) pattern by using multi-temporal satellite data over a period of time. Further, these detected changes in different LULC class influence the livelihoods of forest-dependent communities. As the study site is a Sal dominated landscape; the findings could be applied in other Sal dominated landscape of central India in making future policies, adaptation strategies and silvicultural practices for reducing the vulnerability of forest-dependent communities.</p>

scholarly journals Land Use and Land Cover Change Detection and Prediction in the Kathmandu District of Nepal Using Remote Sensing and GIS

2020 ◽  
Vol 12 (9) ◽  
pp. 3925 ◽  
Author(s):  
Sonam Wangyel Wang ◽  
Belay Manjur Gebru ◽  
Munkhnasan Lamchin ◽  
Rijan Bhakta Kayastha ◽  
Woo-Kyun Lee
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Agricultural Land ◽  
Water Bodies ◽  
Geographical Information ◽  
Land Cover Changes ◽  
Rapid Urbanization ◽  
Urbanized Areas

Understanding land use and land cover changes has become a necessity in managing and monitoring natural resources and development especially urban planning. Remote sensing and geographical information systems are proven tools for assessing land use and land cover changes that help planners to advance sustainability. Our study used remote sensing and geographical information system to detect and predict land use and land cover changes in one of the world’s most vulnerable and rapidly growing city of Kathmandu in Nepal. We found that over a period of 20 years (from 1990 to 2010), the Kathmandu district has lost 9.28% of its forests, 9.80% of its agricultural land and 77% of its water bodies. Significant amounts of these losses have been absorbed by the expanding urbanized areas, which has gained 52.47% of land. Predictions of land use and land cover change trends for 2030 show worsening trends with forest, agriculture and water bodies to decrease by an additional 14.43%, 16.67% and 25.83%, respectively. The highest gain in 2030 is predicted for urbanized areas at 18.55%. Rapid urbanization—coupled with lack of proper planning and high rural-urban migration—is the key driver of these changes. These changes are associated with loss of ecosystem services which will negatively impact human wellbeing in the city. We recommend city planners to mainstream ecosystem-based adaptation and mitigation into urban plans supported by strong policy and funds.

Investigating land use and land cover changes in Dublin, Ireland using Satellite Imagery: A comparative analysis

2020 ◽  
Author(s):  
Bidroha Basu ◽  
Arunima Sarkar Basu ◽  
Srikanta Sannigrahi ◽  
Francesco Pilla
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Population Growth ◽  
Satellite Imagery ◽  
Rainfall Runoff ◽  
Lulc Changes ◽  
The Past ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Over Time

&lt;p&gt;Over the past few decades, there has been over increasing pressure on land due to population growth, urbanization, agriculture expansion and industrialization. The change in land use and land cover (LULC) pattern are highly dependent on human intervention. Deforestation pattern has started due to growth of suburbs, cities, and industrial land. The alarming rate in change of LULC pattern was on a rising trend since 1990s and has been increasing over time. This study focuses on analyzing the changes in LULC pattern in Dublin, Ireland over the past two decades using remotely sensed LANDSAT satellite imagery data, and quantify the effect of LULC change in streamflow simulation in watershed at Dublin by using rainfall-runoff model. Benefit of using remotely sensed image to investigate LULC changes include availability of high-resolution spatial data at free of cost, images captured at high temporal resolution to monitor the changes in LULC during both seasonal and yearly timescale and readily availability of data. The potential classification of landforms has been done by performing both supervised as well as unsupervised classification. The results obtained from the classified images have been compared to google earth images to understand the accuracy of the image classification. The change in LULC can be characterized by changes in building density and urban/artificial area (build up areas increase due to population growth), changes in vegetation area as well as vegetation health, changes in waterbodies and barren land. Furthermore, a set of indices such as vegetation index, building index, water index and drought index were estimated, and their changes were monitored over time. Results of this analysis can be used to understand the driving factors affecting the changes in LULC and to develop mathematical models to predict future changes in landforms. Soil Water Assessment Tool (SWAT) based rainfall-runoff model were used to simulate the changes in runoff due to the LULC changes in watershed over two decades. The developed framework is highly replicable because of the used LANDSAT data and can be applied to generate essential information for conservation and management of green/forest lands, as well as changes in water availability and water stress in the assessed area.&lt;/p&gt;

scholarly journals Land Use and Land Cover Change Detection Using Remote Geospatial Techniques: A Case Study of an Urban City in Southwestern, Nigeria

2021 ◽  
Vol 21(36) (2) ◽  
pp. 4-14
Author(s):  
Adenike Olayungbo
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Forest Cover ◽  
Anthropogenic Activities ◽  
Geographical Information ◽  
Land Cover Changes ◽  
Southwestern Nigeria ◽  
Urban City ◽  
Wide Range ◽  
Supervised Image Classification

Many cities in developing countries are experiencing ecosystem modification and change. Today, about 10 million hectares of the world’s forest cover have been converted to other land uses. In Nigeria, there is an estimated increase of 8.75 million ha of cropland and decrease of about 1.71 million ha of forest cover between 1995 to 2020, indicating that Nigeria has been undergoing a wide range of land use and land cover changes. This paper analyses the changes in land use/cover in Ila Orangun, Southwestern, Nigeria from 1986 to 2018, with a view to providing adequate information on the pattern and trend of land use and land cover changes for proper monitoring and effective planning. The study utilized satellite images from Landsat 1986, 2002 and 2018. Remote sensing and Geographical Information System techniques as well as supervised image classification method were used to assess the magnitude of changes in the city over the study period. The results show that 26.36% of forest cover and 44.48% of waterbody were lost between the period of 1986 and 2018. There was a rapid increase in crop land by 365.7% and gradual increase in built-up areas by 103.85% at an annual rate of 3.25%. Forest was the only land cover type that recorded a constant reduction in areal extent. The study concluded that the changes in land use and land cover is a result of anthropogenic activities in the study area.

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